5 papers · 1 filter
GIFT: A Framework Towards Global Interpretable Faithful Textual Explanations of Vision Classifiers
Ãloi Zablocki, Valentin Gerard, Amaia Cardiel +3
Understanding the decision processes of deep vision models is essential for their safe and trustworthy deployment in real-world settings. Existing explainability approaches, such a…
Halton Scheduler For Masked Generative Image Transformer
Victor Besnier, Mickael Chen, David Hurych +2
Masked Generative Image Transformers (MaskGIT) have emerged as a scalable and efficient image generation framework, able to deliver high-quality visuals with low inference costs. H…
PAFUSE: Part-based Diffusion for 3D Whole-Body Pose Estimation
Nermin Samet, Cédric Rommel, David Picard +1
We introduce a novel approach for 3D whole-body pose estimation, addressing the challenge of scale -- and deformability -- variance across body parts brought by the challenge of ex…
ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation
Cédric Rommel, Victor Letzelter, Nermin Samet +4
We propose ManiPose, a manifold-constrained multi-hypothesis model for human-pose 2D-to-3D lifting. We provide theoretical and empirical evidence that, due to the depth ambiguity i…
Valeo4Cast: A Modular Approach to End-to-End Forecasting
Yihong Xu, Ãloi Zablocki, Alexandre Boulch +11
Motion forecasting is crucial in autonomous driving systems to anticipate the future trajectories of surrounding agents such as pedestrians, vehicles, and traffic signals. In end-t…